Recommendation Engine (Hybrid)
A hybrid recommender combining collaborative and content-based filtering with evaluation metrics.
What this project does
A hybrid recommender combining collaborative and content-based filtering with evaluation metrics.
- Hybrid model
- Cold-start handling
- Evaluation report
Technology stack
We can adapt the stack to your college guidelines — mention any required language, framework or tool in your request.
Who this project suits
At medium difficulty this works well for B.E / B.Tech final-year and major projects, and M.Tech / MCA projects with a focused scope. It's entirely software, so there's no hardware to arrange.
What you receive
- Complete working project (code / design files)
- Technical documentation — architecture, setup & code walkthrough
- Output demo you can run and explain
- Doubt-clearing support while you prepare
Optional add-ons: Project report ₹799 · Presentation (PPT) ₹699 · Report + PPT ₹1,299 · Research paper ₹2,499 · Report + PPT + Research paper ₹3,000.
Questions
Can I customise the Recommendation Engine (Hybrid) project?
Yes. Add or remove features, change the Python / Surprise / PyTorch stack or adjust the scope in the request form — we quote the version you want.
How long does the Recommendation Engine (Hybrid) project take?
Typically around 6 weeks for the standard scope. Share your deadline and we'll tell you honestly if it fits.
What documentation do I receive?
Technical documentation is free with the project — architecture, setup guide and code walkthrough. A project report, PPT and research paper are optional add-ons.
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